About: covid:PMC7250598

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An Entity of Type : owl:Thing, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
Creator	Chen, Yue Cheng, Gong Cochez, Michael Gentile, Anna Haase, Peter Harth, Andreas Kirrane, Sabrina Liu, Qingxia Ngonga Ngomo, Axel-Cyrille Paulheim, Heiko Qu, Yuzhong Rula, Anisa Kharlamov, Evgeny Li, Junyou
is schema:about of	named entity 'Entity' named entity 'FEEDBACK' named entity 'validation set' named entity 'LDA' named entity 'interdependence' named entity 'user feedback' named entity 'interdependence' named entity 'Latent Dirichlet Allocation' named entity 'learning rate' named entity 'learning to rank' named entity 'reinforcement learning' named entity 'semantics' named entity 'triples' named entity 'Markov decision process' named entity 'discrete time' named entity 'discount factor' named entity 'deep neural network' named entity 'learning to rank' named entity 'uSer fEeDback' named entity 'Labeled Data' named entity 'document retrieval' named entity 'document retrieval' named entity 'learning to rank' named entity 'knowledge graph' named entity 'range of 0-1' named entity 'triples' named entity 't-test' named entity 'user feedback' named entity 'neural network' named entity 'reinforcement learning' named entity 'interdependence' named entity 'triples' named entity 'vector space model' named entity 'triples' named entity 'triples' named entity 'deep neural network' named entity 'positive feedback' named entity 'user feedback' named entity 'triples' named entity 'negative feedback' named entity 'Solson Publications' named entity 'learning algorithm' named entity 'statistical significant' named entity 'Google' named entity 'RDF' named entity 'blank node' named entity 'triples' named entity 'Relevance Feedback' named entity 'triples' named entity 'triples' named entity 'RDF' named entity 'triples' named entity 'range of 0-1' named entity 'User Feedback' named entity 'computing' named entity 'user feedback' named entity 'triples' named entity 'formal model' named entity 'user feedback' named entity 'LDA' named entity 'user feedback' named entity 'vector representations' named entity 'deep neural network' named entity 'interdependence' named entity 'training set' named entity 'triples' named entity 'RDF' named entity 'document retrieval' named entity 'triples' named entity 'triples' named entity 'semantics' named entity 'user feedback' named entity 'discount-rate' named entity 'User feedback' named entity 'labeled data' named entity 'policy gradient method' named entity 'relevance feedback' named entity 'interdependence' named entity 'reinforcement learning agent' named entity 'within-subject design' named entity 'Relevance feedback' named entity 'user feedback' named entity 'user feedback' named entity 'vector representations' named entity 'user feedback' named entity 'triples'

Attributes

Values

Creator

Chen, Yue
Cheng, Gong
Cochez, Michael
Gentile, Anna
Haase, Peter
Harth, Andreas
Kirrane, Sabrina
Liu, Qingxia
Ngonga Ngomo, Axel-Cyrille
Paulheim, Heiko
Qu, Yuzhong
Rula, Anisa
Kharlamov, Evgeny
Li, Junyou

is schema:about of

named entity 'Entity'
named entity 'FEEDBACK'
named entity 'validation set'
named entity 'LDA'
named entity 'interdependence'
named entity 'user feedback'
named entity 'interdependence'
named entity 'Latent Dirichlet Allocation'
named entity 'learning rate'
named entity 'learning to rank'
named entity 'reinforcement learning'
named entity 'semantics'
named entity 'triples'
named entity 'Markov decision process'
named entity 'discrete time'
named entity 'discount factor'
named entity 'deep neural network'
named entity 'learning to rank'
named entity 'uSer fEeDback'
named entity 'Labeled Data'
named entity 'document retrieval'
named entity 'document retrieval'
named entity 'learning to rank'
named entity 'knowledge graph'
named entity 'range of 0-1'
named entity 'triples'
named entity 't-test'
named entity 'user feedback'
named entity 'neural network'
named entity 'reinforcement learning'
named entity 'interdependence'
named entity 'triples'
named entity 'vector space model'
named entity 'triples'
named entity 'triples'
named entity 'deep neural network'
named entity 'positive feedback'
named entity 'user feedback'
named entity 'triples'
named entity 'negative feedback'
named entity 'Solson Publications'
named entity 'learning algorithm'
named entity 'statistical significant'
named entity 'Google'
named entity 'RDF'
named entity 'blank node'
named entity 'triples'
named entity 'Relevance Feedback'
named entity 'triples'
named entity 'triples'
named entity 'RDF'
named entity 'triples'
named entity 'range of 0-1'
named entity 'User Feedback'
named entity 'computing'
named entity 'user feedback'
named entity 'triples'
named entity 'formal model'
named entity 'user feedback'
named entity 'LDA'
named entity 'user feedback'
named entity 'vector representations'
named entity 'deep neural network'
named entity 'interdependence'
named entity 'training set'
named entity 'triples'
named entity 'RDF'
named entity 'document retrieval'
named entity 'triples'
named entity 'triples'
named entity 'semantics'
named entity 'user feedback'
named entity 'discount-rate'
named entity 'User feedback'
named entity 'labeled data'
named entity 'policy gradient method'
named entity 'relevance feedback'
named entity 'interdependence'
named entity 'reinforcement learning agent'
named entity 'within-subject design'
named entity 'Relevance feedback'
named entity 'user feedback'
named entity 'user feedback'
named entity 'vector representations'
named entity 'user feedback'
named entity 'triples'

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